Data were analyzed using SPSS 15.0 statistical package for Windows (SPSS Inc., Chicago, IL, USA) and expressed as mean ± standard deviation or as median value (±inter-quartile range) for data that showed skewed distribution. Differences between mean values were assessed by using unpaired t-test for two groups and data that showed skewed distributions were compared with Mann-Whitney U-test. Correlations between variables were defined by Spearman coefficient and the relationships between categorical variables were defined by chi-square tests. p values less than 0.05 were considered significant. ROC curve analysis was used for the determination of ox-LDL cut off point related to systolic cardiac dysfunction. We built models by using logistic regression analysis examining the role of ox-LDL on cardiovascular disease manifestations adjusting for traditional and specific covariates for hemodialysis patients.
Spss 15.0 statistical package for windows
Manufactured by IBM
Sourced in United States
SPSS 15.0 is a statistical software package designed for Windows. It provides data analysis, data management, and data documentation capabilities. The software allows users to perform a variety of statistical analyses, including descriptive statistics, bivariate statistics, and multivariate statistics.
Automatically generated - may contain errors
Lab products found in correlation
7 protocols using spss 15.0 statistical package for windows
1
Oxidized LDL and Cardiac Dysfunction
2
Comparative Analysis of Treatment Efficacy
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All data were expressed as mean ± SD. All analyses utilized SPSS 15.0 statistical package for Windows (SPSS Inc., Chicago, IL). A 1-way analysis of variance (ANOVA) was used for comparisons of means of the different groups. A P-value < .05 was accepted as statistically significant with the least significant difference (LSD) test as the post hoc test. The Spearman rank correlation test was used for the assessment of the correlation. The statistical significance was accepted as P-value < .05.
3
Bacterial Abundance Analysis in Periodontal Pathogens
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The statistical analysis was performed using the SPSS 15.0 statistical package for Windows (SPSS Inc., Chicago, IL, USA). The bacterial copy count of each periodontal pathogen and proportion of each bacterium to the total copy count were compared using the Kruskal–Wallis tests. Tukey’s HSD test was used to assess the difference in each group as post hoc tests. P-values of < 0.05 were considered significant.
4
Carotid Wall Attenuation Analysis
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For the analysis of the data, averaged HU values between unenhanced and early arterial and delayed phase were calculated. Friedman's test was used to correlate averaged HU values and the difference of the carotid wall between pre-contrast and contrast-enhanced phases within each symptomatic and asymptomatic group. The Wilcoxon signed-rank correlation test was used to test averaged HU values and difference between symptomatic and asymptomatic groups. Differences were defined as significant at a probability level <0.05. All analyses were performed using the SPSS 15.0 statistical package for Windows (SPSS Inc., Chicago, IL, USA).
5
Asthma Biomarkers and Smoking Impacts
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Variables are presented as the mean ± SD or median (IQR) according to data distribution determined by the Kolmogorov-Smirnoff test. T test or Mann–Whitney tests were used to compare groups (asthma vs. control, smoking vs. non-smoking asthma patients). The correlations were analysed by the Spearman or Pearson tests, depending on the distribution of the sample. Values p < 0.05 were considered statistically significant. Analyses were performed using the SPSS 15.0 statistical package for Windows (SPSS Inc., Chicago, IL, USA).
6
Determinants of Beta-2 Microglobulin in Dialysis Patients
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Data was analyzed using SPSS 15.0 statistical package for Windows (SPSS Inc, Chicago, Illinois) and expressed as mean ± standard deviation or as median value ± interquartile range for data that showed skewed distributions; differences between mean values were assessed by using paired-t test and Mann–Whitney U test. Correlations between variables were defined by Pearson and Spearman coefficient and p values less than .05 were considered significant. x2 analysis was used for the correlation between categorical variables.We built a linear regression analysis to investigate if glucose serum concentrations could be a potential determinant of beta2M serum levels in dialysis patients adjusting for age, gender, dialysis modality and metabolic acidosis state.
7
Visceral Obesity and Albuminuria
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Data were analyzed using SPSS 15.0 Statistical Package for Windows (SPSS Inc, Chicago, Illinois, USA) and expressed as mean ± standard deviation or as median value ± interquartile range for data that showed skewed distribution. Differences between mean values were assessed by using unpaired t-test for two groups and data that showed skewed distributions were compared with Mann-Whitney U-test.
Correlations between categorical variables were defined by Chi-square tests. P values less than 0.05 were considered significant. We built a model using linear regression analysis by enter method for the role of visceral obesity on the development of albuminuria adjusting for covariates including age, gender, BMI, DM, triglycerides, HTN, eGFR value, and WC. Power calculation was per-formed at the end of the study using the Power and Precision statistical package (version 3.0, Biostat, Englewood, NJ, USA) and the sample size was sufficient.
Correlations between categorical variables were defined by Chi-square tests. P values less than 0.05 were considered significant. We built a model using linear regression analysis by enter method for the role of visceral obesity on the development of albuminuria adjusting for covariates including age, gender, BMI, DM, triglycerides, HTN, eGFR value, and WC. Power calculation was per-formed at the end of the study using the Power and Precision statistical package (version 3.0, Biostat, Englewood, NJ, USA) and the sample size was sufficient.
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